Environment perception and recognition can be realized via deep learning and Convolutional Neural Networks (CNN). The perception and recognition can include capturing views of the surrounding environment and classifying objects in the views. Wide-angle cameras can increase the captured field-of-view, however these cameras produce a “fisheye” effect. The fisheye effect results in a distorted image, where the distortion is dependent on a distance from the camera center. Objects closer to the camera center appear normal, while objects farther from the camera center are distorted with a convex non-rectilinear appearance. This distortion can prevent deep learning and CNNs from accurately perceiving, recognizing, and classifying the surrounding environment.
The same numbers are used throughout the disclosure and the figures to reference like components and features. Numbers in the 100 series refer to features originally found in FIG. 1; numbers in the 200 series refer to features originally found in FIG. 2; and so on.